A recent article from Forbes seems to indicate that low volatility stocks outperform high volatility stocks over the long run. Does anyone have any supporting or contradicting evidence to this claim? The study cited studied returns for the entire stock market and the 1,000 largest stocks from 1968 to 2008.

Note that the answer to this question is really a simple yes or no, however the larger issue is whether or not the period under study was cherry picked and if different results would have been obtained using different end dates.

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chrisaycockMar 12 '11 at 22:42

I'm guessing that averaging down on a high volatility stock is a better investment than averaging down (or buying outright) a low volatility stock.
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barrycarterMar 13 '11 at 2:04

no, but returns are supposed to be easier to predict
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RockScienceApr 1 '11 at 5:13

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For idiosyncratic volatility (e.g. standard deviation of residuals of the CAPM), the consensus seems to be that the question is not settled. Evidence is contradictory. For example Ang et al. (2006, 2009) find a negative relationship, but many others find a positive relationship. I am unfamiliar with the literature on using the returns standard deviation as the volatility though.
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JaseOct 28 '12 at 13:24

4 Answers
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Empirically, standard, intuitive measures of risk like volatility and beta do not generate a positive correlation with average returns in most asset classes. It is possible that risk, however defined, is not positively related to return as an equilibrium in asset markets. This paper presents a survey of data across 20 different asset classes, and presents a model highlighting the assumptions consistent with no risk premium. The key is that when agents are concerned about relative wealth, risk taking is then deviating from the consensus or market portfolio. In this environment, all risk becomes like idiosyncratic risk in the standard model, avoidable so unpriced.

The theory predicts that expected risk and expected return should be positively related. But no one has convincingly proved this. The results are very sensitive to how you determine the expectations of risk and return and the timeline you use. Many have shown that there isn't a positive trade-off between risk and return in a CAPM-framework (i.e., Fama and French 1992 showed that $\beta$ has no predictive power in the cross section of returns -- although in 1993 they "saved" $\beta$ by adding two more factors).

What is odd about this Baker et al research is that they're buying the 20% with the highest vol and holding them for only one year. They're are constantly investing in the most uncertain stocks without ever really allowing the uncertainty to get resolved. I would be interested in how these results change with a two to five year holding period (e.g., I imagine in the mid 90s both amazon.com and pets.com where volatile; if you held both for one year, then you may or may not come out ahead; but if you held both for five years, pets.com delists and amazon.com skyrockets; but this is anecdotal and far from convincing.)

In my thesis I have found both unconditional return volatility (standard deviation) and idiosyncratic risk w.r.t. a market model to be the most consistent determinants of whether a stock falls during a crisis or a crash.
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user2921Sep 30 '12 at 12:35

Nice. Do you know if there are any counter-examples where research shows that historical standard deviation of returns is related to strong future performance? Or is there consensus on this issue that low standard deviation --> high returns? (I'm not talking about idiosyncratic volatility).
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JaseOct 28 '12 at 14:59

Antti Ilmanen in his book Expected Returns shows this phenomenon in assets in addition to equities. So it seems to be a general phenomenon rather than due to a cherry-picked example.

He also discusses (page 393) an explanation in addition to the lottery idea. Investors that can not leverage but who seek higher returns will overweight high volatility assets. This will tend to drive up their prices and hence drive down their expected returns.